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It has recently been demonstrated that locality of spatial supports in the parametrization of coefficients in elliptic PDEs can lead to improved convergence rates of sparse polynomial expansions of the corresponding parameter-dependent…

Numerical Analysis · Mathematics 2017-07-11 Markus Bachmayr , Albert Cohen , Dinh Dũng , Christoph Schwab

A numerical analysis for the fully discrete approximation of an operator Lyapunov equation related to linear SPDEs (stochastic partial differential equations) driven by multiplicative noise is considered. The discretization of the Lyapunov…

Numerical Analysis · Mathematics 2022-05-04 Adam Andersson , Annika Lang , Andreas Petersson , Leander Schroer

In 2002, Evertse and Schlickewei obtained a quantitative version of the so-called Absolute Parametric Subspace Theorem. This result deals with a parametrized class of twisted heights. One of the consequences of this result is a quantitative…

Number Theory · Mathematics 2023-09-19 Jan-Hendrik Evertse , Roberto G. Ferretti

We establish the dual notions of scaling and saturation from geometric control theory in an infinite-dimensional setting. This generalization is applied to the low-mode control problem in a number of concrete nonlinear partial differential…

Probability · Mathematics 2018-09-21 Nathan E. Glatt-Holtz , David P. Herzog , Jonathan C. Mattingly

A stochastic PDE, describing mesoscopic fluctuations in systems of weakly interacting inertial particles of finite volume, is proposed and analysed in any finite dimension $d\in\mathbb{N}$. It is a regularised and inertial version of the…

Analysis of PDEs · Mathematics 2021-02-10 Federico Cornalba , Tony Shardlow , Johannes Zimmer

Many geometric and analytic properties of sets hinge on the properties of harmonic measure, notoriously missing for sets of higher co-dimension. The aim of this manuscript is to develop a version of elliptic theory, associated to a linear…

Analysis of PDEs · Mathematics 2023-09-26 Guy R. David , Joseph Feneuil , Svitlana Mayboroda

Motivated by recent applications of Carroll symmetries we investigate the geometry of flat and curved (AdS) Carroll space and the symmetries of a particle moving in such a space both in the bosonic as well as in the supersymmetric case. In…

High Energy Physics - Theory · Physics 2016-04-20 Eric Bergshoeff , Joaquim Gomis , Lorena Parra

This paper deals with the numerical approximation of semilinear parabolic stochastic partial differential equation (SPDE) driven simultaneously by Gaussian noise and Poisson random measure, more realistic in modeling real world phenomena.…

Numerical Analysis · Mathematics 2020-11-19 Jean Daniel Mukam , Antoine Tambue

The notion of ellipsoidal design was first introduced by Pandey (2022) as a full generalization of spherical designs on the unit circle $S^1$. In this paper, we elucidate the advantages of examining the connections between ellipsoidal…

Combinatorics · Mathematics 2025-04-30 Hideki Matsumura , Masanori Sawa

We consider the problem of embedding a finite set of points $\{x_1, \ldots, x_n\} \in \mathbb{R}^d$ that satisfy $\ell_2^2$ triangle inequalities into $\ell_1$, when the points are approximately low-dimensional. Goemans (unpublished,…

Data Structures and Algorithms · Computer Science 2017-06-22 Yuval Rabani , Rakesh Venkat

In this paper, we introduce a numerical solution of a stochastic partial differential equation (SPDE) of elliptic type using polynomial chaos along side with polynomial approximation at Sinc points. These Sinc points are defined by a…

Numerical Analysis · Mathematics 2019-04-08 Maha Youssef , Roland Pulch

We introduce and study finite $d$-volumes - the high dimensional generalization of finite metric spaces. Having developed a suitable combinatorial machinery, we define $\ell_1$-volumes and show that they contain Euclidean volumes and…

Data Structures and Algorithms · Computer Science 2010-08-03 Ilan Newman , Yuri Rabinovich

We discuss mathematical methods to derive Nonlinear Schr\"odinger equations (NLS) in "low dimensional" settings, i.e. the 3-dimensional physical space e.g. to 2 or 1 space dimensions. Beside from the case the system exhibits an internal…

Computational Physics · Physics 2023-12-19 Peter Allmer

Partial Least Squares (PLS) refer to a class of dimension-reduction techniques aiming at the identification of two sets of components with maximal covariance, to model the relationship between two sets of observed variables…

Methodology · Statistics 2023-02-23 Lola Etievant , Vivian Viallon

We establish well-posedness and maximal regularity estimates for linear parabolic SPDE in divergence form involving random coefficients that are merely bounded and measurable in the time, space, and probability variables. To reach this…

Analysis of PDEs · Mathematics 2023-10-17 Pascal Auscher , Pierre Portal

We establish existence and qualitative properties of saddle-shaped solutions of the elliptic fractional equation $(-\Delta)^{1/2}u=f(u)$ in all the space $\re^{2m}$, where $f$ is of bistable type. These solutions are odd with respect to the…

Analysis of PDEs · Mathematics 2011-07-13 Eleonora Cinti

The first quantized theory of N=2, D=3 massive superparticles with arbitrary fixed central charge and (half)integer or fractional superspin is constructed. The quantum states are realized on the fields carrying a finite dimensional, or a…

High Energy Physics - Theory · Physics 2009-10-31 I. V. Gorbunov , S. L. Lyakhovich

The $l_2$ flattening lemma of Johnson and Lindenstrauss [JL84] is a powerful tool for dimension reduction. It has been conjectured that the target dimension bounds can be refined and bounded in terms of the intrinsic dimensionality of the…

Computational Geometry · Computer Science 2015-06-09 Lee-Ad Gottlieb , Robert Krauthgamer

Gravitational waves with a space-translation Killing field are considered. In this case, the 4-dimensional Einstein vacuum equations are equivalent to the 3-dimensional Einstein equations with certain matter sources. This interplay between…

General Relativity and Quantum Cosmology · Physics 2014-11-17 Abhay Ashtekar , Jiri Bicak , Bernd G. Schmidt

In this paper, we introduce principal asymmetric least squares (PALS) as a unified framework for linear and nonlinear sufficient dimension reduction. Classical methods such as sliced inverse regression (Li, 1991) and principal support…

Statistics Theory · Mathematics 2020-02-14 Abdul-Nasah Soale , Yuexiao Dong